Developer Portal

The EDB Developer Portal provides learning and operational guidance not just by product, but by the foundational technologies that power the entire EDB ecosystem. This section focuses on the core platforms and patterns used across solutions—including Kubernetes, Postgres, and emerging AI infrastructure.

These technologies form the substrate of everything from database orchestration to generative AI, model serving, vector search, and observability. Whether you’re running Hybrid Manager, building with AI Factory, or managing large-scale Postgres clusters, these systems provide the operational backbone.

Kubernetes

Kubernetes is the orchestration engine that underpins many EDB workloads. It’s used to:

• Run containerized Postgres clusters
• Deploy AI Factory workloads (Gen AI assistants, model serving, vector search)
• Enable observability, scaling, and platform automation
• Support Hybrid Manager across cloud and on-prem deployments

Get started with:

• Kubernetes at EDB
• Kubernetes in Hybrid Manager
• Kubernetes How-To Guides

Postgres (Coming Soon)

Postgres is the core data engine across all EDB solutions. This section will cover:

• Postgres internals and architecture
• High availability, backups, and performance tuning
• Extensions, logical replication, and clustering
• Managing Postgres in containers and Kubernetes

Guides and architectural patterns for Postgres will be added to this section as it expands.

AI (Coming Soon)

This section will capture the shared that powers AI and ML workloads at EDB:

• Model Serving patterns and GPU provisioning
• Vector-enabled search systems
• Retrieval-augmented generation (RAG) infrastructure
• Pipelines for embedding and document processing
• Scaling and governance of Gen AI features

These guides will help platform teams and AI architects deploy reusable patterns across products like AI Factory and Hybrid Manager.

Why This Section Exists

While most content on the Developer Portal is organized by product and workload, this section helps you:

• Build mental models around the core tech layers
• Understand operational responsibilities that cut across products
• Implement consistent patterns across environments and teams
• Navigate foundational concerns like security, automation, and performance